In [1]:
import numpy as np
import pandas as pd
import folium as fo
%matplotlib inline
In [8]:
map = fo.Map()
map
Out[8]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [5]:
popu = pd.read_csv('C:\\Users\\hp\\Desktop\\Programming Software\\Programs\\Python Notes\\241.us+cities+pop.csv')
popu.head()
Out[5]:
name pop lat lon
0 New York 8287238 40.730599 -73.986581
1 Los Angeles 3826423 34.053717 -118.242727
2 Chicago 2705627 41.875555 -87.624421
3 Houston 2129784 29.758938 -95.367697
4 Philadelphia 1539313 39.952335 -75.163789
In [7]:
lat_po = list(popu['lat'])
lan_po = list(popu['lon'])
name_po = list(popu['name'])
pop_po = list(popu['pop'])
po = fo.FeatureGroup(name='My Map')
for lat,lon,name,pop in zip(lat_po,lan_po,name_po,pop_po):
    po.add_child(fo.Marker(location=[lat,lon],popup=[pop,name],icon=fo.Icon(color='blue')))
map.add_child(po)
Out[7]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [10]:
lat_po = list(popu['lat'])
lan_po = list(popu['lon'])
name_po = list(popu['name'])
pop_po = list(popu['pop'])
po = fo.FeatureGroup(name='My Map')
def mar(popu):
    if(pop>35000):
        return 'red'
    elif(popu>10000 and popu<=35000):
        return 'blue'
    else:
        return 'green'
for lat,lon,name,pop in zip(lat_po,lan_po,name_po,pop_po):
    po.add_child(fo.Marker(location=[lat,lon],popup=[pop,name],icon=fo.Icon(color=mar(pop))))
map.add_child(po)
Out[10]:
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